With over 30 years of business intelligence experience — and as the founder and CEO of a consulting company — I have helped enterprises in an array of sectors, including banking, health care and integrated resorts. My experience with intelligence platforms has enabled me to clearly identify areas needing improvement to increase efficiency, as well as assess which elements to focus on when planning and implementing change.
There are five essential building blocks to creating a solution that avoids costly impediments to success. The result of having this foundation in place is having data that is reliably collected with an automated workflow so that advanced algorithms can be applied. Reliable data freed from siloes provides access to inform how your company is performing. This is also the first step to having a holistic data hub and an efficient, productive company.
These are the five essential building blocks designed to guide the transformation to a lean, agile and productive enterprise:
1. Consolidate all source systems into one centralized data hub.
Consolidation is the start of getting a holistic view of your company, discovering new key performance indicators and gaining insights into lines of business to help decision-making. To ensure successful consolidation, collaborate with the stakeholders within your organization who rely on data for decision-making and enterprise-level reporting, and the CIO or IT team.
Ask how much of an impact it would be if managers could make faster, better decisions and if the IT department could be relieved of endless requests for report production. The IT team will be able to make recommendations that will be received favorably in terms of capital expense if a value can be placed on the project. There needs to be enterprise-wide consensus and acceptance of the consolidation effort.
2. Structure your data for easy consumption by different lines of businesses and departments.
The consolidation of data ensures the reliability of enterprise reporting for operators and managers. Now it’s time for you to structure that data.
Data needs to be structured so that you can extract insights that are relevant to the KPIs you care about. For example, a floor manager at an integrated resort might want insights into the revenue performance of slot machines, machine malfunctions, slot machine placement and daily coin-in revenue. The food and beverage manager might be interested to know the daily tickets served and staffing requirements, and the hotel and hospitality manager would need to report revenue based on reservations.
Each manager in your organization has different reporting needs for insights, while at the enterprise level those reports have to provide a complete and holistic picture to be actionable and provide the efficiency sought after. Structure your data in a way that enables insights to be extracted from questions unique to each operator of a line of business. These operators are the best ones to determine which questions to ask, and they are also able to put the answers to the questions to work right away.
3. Deploy innovative technologies to extract not-so-obvious actionable insights.
The key to actionable insights is how the data is extracted, and new technologies like artificial intelligence and machine learning can help. (A number of companies, my own included, provide this type of technology.)
Advanced analytics provide predictive and prescriptive analytics, which are the most valuable part of the solution. Although it will all come down to the data when deploying intelligent solutions, it is at the beginning when ingoing assumptions of those KPIs are established on what can be automated. Involving key stakeholders and IT in this conversation is key. Stakeholders will identify what data points they need to make better decisions, and IT will know where that data resides and any issues getting to it.
It’s important to note that challenges often arise when data is part of outdated legacy software or platforms, so stakeholders might not want to give up today’s familiarity. Ask your IT team to detail the process of moving away from these legacy systems.
4. Implement automated workflow systems where needed.
Efficiencies are manifest as automated workflow systems replace routines and systems processes that might be baked in due to legacy systems constraints or departmental and line-of-business needs. End users know when they are doing repetitive work and seeing redundancies, so it’s important to create a corporate culture that makes employees feel empowered to speak up about where improvements can be made.
5. Find the software solution that fits your needs.
Not all of the 50 or so solution platforms are the same. As you can imagine, they come with different strengths and uses. You’ll be surprised to learn that many of the business intelligence tools can match very specific needs and come close to performing close to custom-tailored software. However, you might find a custom solution is what your company needs.
If you are considering getting an audit from a consulting company, be prepared to articulate your exact needs and reasons for adding the technology. Assess the solutions and best practices that have been adopted within your business sector recently. Ask questions about flexibility and functionality based on your needs. For example: Will it connect with all the software you are currently using? Is it is scalable? Are there data limitations? Will people use it? Does the company provide support, training and consultative services?
In conclusion, the goal of creating a more competitive and efficient company is easier to achieve with software that’s able to collect data at nearly all consumer touchpoints. However, business systems now in place are being choked by massive volumes of data that are siloed, which prevents the extraction of insights by the line of business for fast and accurate decision-making. Right now, companies can avoid costly, laborious and repetitive processes by having these building blocks in place.